“Science is to test crazy ideas – Engineering is to put these into Business”
Assoc.Prof.Dr. Andreas HOLZINGER
PhD, MSc, MPh, BEng, CEng, DipEd, MBCS
Holzinger Group HCI-KDD
Institute for Medical Informatics, Statistics & Documentation
Medical University Graz, and
Institute of Interactive Systems and Data Science
Graz University of Technology
The Holzinger group is doing theoretical, algorithmical, and experimental studies to help to understand the problem of knowledge extraction from complex data to discover unknown unknowns. The challenge is to help the international research community to answer a grand question: How can we perform a task by exploiting knowledge, extracted during solving previous tasks? Contributions to this problem would have major impact to Artificial Intelligence generally, and Machine Learning specifically, to develop software which learns from previous experience – similarly as we humans do.
Our goal is to develop software which can learn from data to extract knowledge and improve with experience over time. However, the application of such automatic machine learning (aML) algorithms in complex domains (e.g. Health) seems elusive in the near future, and a good example are Gaussian processes, where aML (e.g. standard kernel machines) struggle on function extrapolation problems which are trivial for human learners.
Consequently, interactive machine learning (iML) with a human-in-the-loop, thereby making use of human cognitive abilities, can be of particular interest to solve problems, where learning algorithms suffer due to insufficient training samples, where we deal with complex data and/or rare events or computationally hard problems.
A “doctor-in-the-loop” can help, and human expertise and long-term experience can assist in solving problems which otherwise would remain NP-hard. However, successful MAchine learning and Knowledge Extraction (MAKE) for health informatics requires a deep understanding of the data ecosystem and a concerted effort cross-domain of 7 research topics: 1) data integration, 2) learning algorithms, 3) graphs, 4) topology, 5) entropy, 6) visualization, and 7) privacy, data protection, safety and security.
Consequently, Andreas and his Group work on a synergistic combination of methodologies of two areas that offer ideal conditions towards unraveling such problems: Human-Computer Interaction (HCI) and Knowledge Discovery/Data Mining (KDD), with the goal of supporting human intelligence with machine learning to discover novel, previously unknown insights into data. Andreas is passionate on extending advanced methods including time (e.g. information entropy) and space (e.g. computational topology), along with user-centered software engineering to create interactive algorithms and tools for data science. Andreas is founder of the Expert Network HCI-KDD and Assoc. Editor of Knowledge and Information Systems (KAIS) and Brain Informatics (BRIN), and member of IFIP WG 12.9 Computational Intelligence.
Workareas and Research Topics of the Holzinger Group > hci-kdd.org.
We are conducting theoretical, algorithmical, and experimental studies to understand intelligence.
Technical Area: Knowledge Discovery/Data Mining, interactive Machine Learning, Cognitive computing
Application Area: Biomedical Informatics, Smart Health, Personalized Medicine
Subjects (OESTAT classification): 11 = Computational Sciences and 39 = Interdisciplinary Human Medicine
Andreas HOLZINGER short biographical statement:
Andreas Holzinger is lead of the Holzinger Group HCI-KDD, Institute for Medical Informatics/Statistics at the Medical University Graz, and Associate Professor of Applied Computer Science at the Faculty of Computer Science and Biomedical Engineering at Graz University of Technology. Currently, Andreas is Visiting Professor for Machine Learning in Health Informatics at the Faculty of Informatics at Vienna University of Technology. He serves as consultant for the Canadian, US, UK, Swiss, French, Italian and Dutch Government, for the German Excellence Initiative and as national expert in the European Commission. His research interests are in supporting human intelligence with machine intelligence to help to solve problems in health informatics. Andreas obtained a Ph.D. in Cognitive Science from Graz University in 1998 and his Habilitation (second Ph.D.) in Computer Science from Graz University of Technology in 2003. Andreas was Visiting Professor in Berlin, Innsbruck, London (2 times), and Aachen. He founded the Expert Network HCI-KDD to foster a synergistic combination of methodologies of two areas that offer ideal conditions toward unraveling problems in understanding intelligence: Human-Computer Interaction (HCI) & Knowledge Discovery/Data Mining (KDD), with the goal of supporting human intelligence with machine learning. Andreas is Associate Editor of Knowledge and Information Systems (KAIS), Section Editor of BMC Medical Informatics and Decision Making (MIDM), and member of IFIP WG 12.9 Computational Intelligence, the ACM, IEEE, GI and the Austrian Computer Science. Since 2003 Andreas has participated in leading positions in 30+ R&D multi-national projects, budget 4+ MEUR, 300+ publications, 7700+ citations, h-Index = 39.
More information see Holzinger Group http://hci-kdd.org/